Here, \(C\)  is the number of channels in a feature map,
\(W_{n,m}\)  are the weights of block \(B_{n,m}\) , \(Y_n\)  is the target output feature map of \(B_n\) , \(Y^{\prime }_{n,m}\)  is the output of block \(B_{n,m}\)  and \(\sigma _{n,c}^2\)  is the variance of \(Y_{n,c}\) . This metric is closely related to Mean-Square-Error (MSE) on the feature maps, which [1]} shows to be correlated to the task loss.
